class_docstr: GRU gate for matrix, similar to the official code.
  Please refer to section 3.4 of the paper for the formula.
code: def __init__(self, rows, cols, activation):
      super().__init__()
      self.activation = activation
      self.W = Parameter(torch.Tensor(rows, rows))
      self.U = Parameter(torch.Tensor(rows, rows))
      self.bias = Parameter(torch.Tensor(rows, cols))
      self.reset_parameters()
  
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import GraphConv
  from torch.nn import init
  from torch.nn.parameter import Parameter
label_desc: Use image node_id 1 to create a new MatGRUGate object from inherited base classes: torch.nn with example: obj = MatGRUGate(rows, cols, activation)